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![LangChain](https://pica.zhimg.com/50/v2-56e8bbb52aa271012541c1fe1ceb11a2_r.gif)



相似度
=====

SemanticSimilarityExampleSelector根据示例与输入的相似度选择示例。它通过查找嵌入与输入的余弦相似度最大的示例来实现此目的。

```python
from langchain.prompts.example_selector import SemanticSimilarityExampleSelector
from langchain.vectorstores import Chroma
from langchain.embeddings import OpenAIEmbeddings
from langchain.prompts import FewShotPromptTemplate, PromptTemplate

example_prompt = PromptTemplate(
    input_variables=["input", "output"],
    template="Input: {input}\nOutput: {output}",
)

# These are a lot of examples of a pretend task of creating antonyms.
examples = [
    {"input": "happy", "output": "sad"},
    {"input": "tall", "output": "short"},
    {"input": "energetic", "output": "lethargic"},
    {"input": "sunny", "output": "gloomy"},
    {"input": "windy", "output": "calm"},
]

```

```python
example_selector = SemanticSimilarityExampleSelector.from_examples(
    # This is the list of examples available to select from.
    examples, 
    # This is the embedding class used to produce embeddings which are used to measure semantic similarity.
    OpenAIEmbeddings(), 
    # This is the VectorStore class that is used to store the embeddings and do a similarity search over.
    Chroma, 
    # This is the number of examples to produce.
    k=1
)
similar_prompt = FewShotPromptTemplate(
    # We provide an ExampleSelector instead of examples.
    example_selector=example_selector,
    example_prompt=example_prompt,
    prefix="Give the antonym of every input",
    suffix="Input: {adjective}\nOutput:", 
    input_variables=["adjective"],
)

```

```python
Running Chroma using direct local API.
Using DuckDB in-memory for database. Data will be transient.

```

```python
# Input is a feeling, so should select the happy/sad example
print(similar_prompt.format(adjective="worried"))

```

```python
Give the antonym of every input

Input: happy
Output: sad

Input: worried
Output:

```

```python
# Input is a measurement, so should select the tall/short example
print(similar_prompt.format(adjective="fat"))

```

```python
Give the antonym of every input

Input: happy
Output: sad

Input: fat
Output:

```

```python
# You can add new examples to the SemanticSimilarityExampleSelector as well
similar_prompt.example_selector.add_example({"input": "enthusiastic", "output": "apathetic"})
print(similar_prompt.format(adjective="joyful"))

```

```python
Give the antonym of every input

Input: happy
Output: sad

Input: joyful
Output:

```

